Protocol for a multicentre randomized controlled trial of normobaric versus hyperbaric oxygen therapy for hypoxemic COVID-19 patients
Notice bibliographique
Résumé
ABSTRACT Background At least 1 in 6 COVID-19 patients admitted to hospital and receiving supplemental oxygen will die of complications. More than 50% of patients with COVID-19 that receive invasive treatment such as mechanical ventilation will die in hospital. Such impacts overwhelm the limited intensive care unit resources and may lead to further deaths given inadequate access to care. Hyperbaric oxygen therapy (HBOT) is defined as breathing 100% oxygen at a pressure higher than 1.4 atmosphere absolute (ATA). HBOT is safe, including for lungs, when administered by experienced teams and is routinely administrated for a number of approved indications. Preliminary clinical evidence suggests clinical improvement when hypoxemic COVID-19 patients are treated with HBOT. Objective We aim to determine the effectiveness of HBOT for improving oxygenation, morbidity, and mortality among hypoxemic COVID-19 patients. Methods and analysis This trial is a sequential Bayesian Parallel-group, individually Randomized, Open, Blinded Endpoint controlled trial. Admitted hypoxemic COVID-19 patients who require supplemental oxygen (without mechanical ventilation) to maintain a satisfying tissue oxygenation will be eligible to participate. The anticipated sample size of 234 patients is informed by data from a treatment trial of COVID patients recently published. The intervention group will receive one HBOT per day at 2.0 ATA for 75 minutes. Daily HBOT will be administered until the patient does not require any oxygen supplementation, requires any type of mechanical ventilation, or until day 10 of treatment. Patients in the control group will receive the current standard of care treatment (no HBOT). The primary outcome of this trial will be the 7-level COVID ordinal outcomes scale assessed on Day 7 post-randomization. Secondary outcomes will include: (a) clinical outcomes (length of hospital stay, days with oxygen supplementation, oxygen flow values to obtain a saturation by pulse oximetry ≥90%, intensive care admission and length of stay, days on invasive mechanical ventilation, sleep quality, fatigue, major thrombotic events, the 7-level COVID ordinal outcomes scale on Day 28; mortality, safety); (b) biological outcomes (plasma inflammatory markers); and (c) health system outcomes (cost of care and cost-effectiveness). Predetermined inclusion/exclusion criteria have been specified. The analytical approach for the primary outcome will use a Bayesian proportional odds ordinal logistic semiparametric model. The primary analysis will be by intention-to-treat. Bayesian posterior probabilities will be calculated every 20 patients to assess accumulating evidence for benefit or harm. A planned subgroup analysis will be performed for pre-specified variables known to impact COVID-19 prognosis and/or HBOT (biologic sex and age). Discussion Based on the mortality rate and substantial burden of COVID-19 on the healthcare system, it is imperative that solutions be found. HBOT is a non-invasive and low-risk intervention when contraindications are respected. The established safety and relatively low cost of providing HBOT along with its potential to improve the prognosis of severe COVID-19 patients make this intervention worth studying, despite the current limited number of HBOT centres. If this trial finds that HBOT significantly improves outcome and prevents further deterioration leading to critical care for severe COVID-19 patients, practice will change internationally. If no benefit is found from the intervention, then the current standard of care (no HBOT) will be supported by level I evidence. Trials Registration NCT04500626
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,037 | 0,045 |
| Méta-épidémiologie (sens strict) | 0,007 | 0,003 |
| Méta-épidémiologie (sens large) | 0,011 | 0,006 |
| Bibliométrie | 0,003 | 0,003 |
| Études des sciences et des technologies | 0,004 | 0,004 |
| Communication savante | 0,004 | 0,003 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,008 | 0,011 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,093 | 0,013 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».